Python Code and Output

Individual Line Chart for all Adani Group companies
fig1 = px.line(df,x = df['date'], y =df['open'], color= 'company', facet_col="company", facet_col_wrap=2)

fig1.show()

Line Chart for all Adani Group companies
fig2 = px.line(df,x = df['date'], y =df['open'], color= 'company', line_group='company', hover_name='company',
        line_shape="spline", render_mode="svg")

fig2.update_xaxes(
    rangeslider_visible=True,
    rangeselector=dict(
        buttons=list([
            dict(count=5, label="5d", step="day", stepmode="backward"),
            dict(count=1, label="1m", step="month", stepmode="backward"),
            dict(count=6, label="6m", step="month", stepmode="backward"),
            dict(count=1, label="YTD", step="year", stepmode="todate"),
            dict(count=1, label="1y", step="year", stepmode="backward"),
            dict(count=5, label="5y", step="year", stepmode="backward"),
            dict(step="all")
        ])
    )
)
fig2.update_layout(title_text='Line Chart')
fig2.update_layout(xaxis_rangeslider_visible=False)
fig2.show()

Area graph for all Adani Group companies
fig3 = px.area(df,x = df['date'], y =df['open'], color= 'company', line_group='company')
fig3.update_layout(title_text='Area graph')
fig3.show()

Individual Histogram for all Adani Group companies
fig4 = px.histogram(df,x = df['date'], y =df['open'], color= 'company',histfunc="avg", facet_col="company", facet_col_wrap=2)
fig4.show()

Histogram for all Adani Group companies
fig5 = px.histogram(df, x="date", y="close",
             color='company', barmode='group',histfunc="avg",
             height=400)
fig5.update_layout(title_text='Histogram')
fig5.show()

Average closing price for all Adani Group companies
fig6 = px.histogram(df, x="date", y="close",
             color='company', barmode='group',histfunc="avg",
             height=400)
fig6.update_layout(title_text='Histogram')
fig6.show()

fig7 = px.histogram(df, x="company", y="close",
             color='company', barmode='group',histfunc="max")
fig7.update_layout(title_text='Max Close Price')

fig7.show()

fig8 = px.histogram(df, x="company", y="close",
             color='company', barmode='group',histfunc="min")
fig8.update_layout(title_text='Min Close Price')

fig8.show()

Candle Stick Visualisation for ACC cements
import plotly.graph_objects as go

fig9 = go.Figure(data=[go.Candlestick(x=df_acc['date'],
                open=df_acc['open'],
                high=df_acc['high'],
                low=df_acc['low'],
                close=df_acc['close'])])

fig9.update_xaxes(
    rangeslider_visible=True,
    rangeselector=dict(
        buttons=list([
            dict(count=1, label="1m", step="month", stepmode="backward"),
            dict(count=6, label="6m", step="month", stepmode="backward"),
            dict(count=1, label="YTD", step="year", stepmode="todate"),
            dict(count=1, label="1y", step="year", stepmode="backward"),
            dict(step="all")
        ])
    )
)
fig9.update_layout(xaxis_rangeslider_visible=False)
fig9.update_layout(title_text='Candle stick')

fig9.show()

Line chart for ACC cements for time-series analysis
import plotly.express as px


fig10 = px.line(df_acc, x=df_acc['date'], y=df_acc['close'])
fig10.update_layout(title_text='Line chart for ACC')

fig10.show()

Line chart for ACC cements with Selectors
fig11 = px.line(df_acc, x='date', y='high', title='Line chart for ACC with selectors')

fig11.update_xaxes(
    rangeslider_visible=True,
    rangeselector=dict(
        buttons=list([
            dict(count=5, label="5d", step="day", stepmode="backward"),
            dict(count=1, label="1m", step="month", stepmode="backward"),
            dict(count=6, label="6m", step="month", stepmode="backward"),
            dict(count=1, label="YTD", step="year", stepmode="todate"),
            dict(count=1, label="1y", step="year", stepmode="backward"),
            dict(count=5, label="5y", step="year", stepmode="backward"),
            dict(step="all")
        ])
    )
)
fig11.update_layout(xaxis_rangeslider_visible=False)

fig11.show()

Area graph for ACC cements
fig12 = px.area(df_acc,x = df_acc['date'], y = df_acc['open'], facet_col_wrap=2)
fig12 = px.area(df_ambuja,x = df_ambuja['date'], y = df_ambuja['open'], facet_col_wrap=2)
fig12.update_layout(title_text='Area graph for ACC')

fig12.show()

Area chart for ACC and Ambuja
fig13 = px.area(vertical_concat,x = vertical_concat['date'], y =vertical_concat['open'], facet_col_wrap=2)
fig13.update_layout(title_text='Area chart for ACC and Ambuja')

fig13.show()

Line chart for ACC and Ambuja
fig14 = px.line(vertical_concat,x = vertical_concat['date'], y =vertical_concat['open'], facet_col="company", facet_col_wrap=2)
fig14.update_layout(title_text='Line chart for ACC and Ambuja')

fig14.show()

Line chart for ACC and Ambuja with selectors
fig15 = px.line(vertical_concat,x = vertical_concat['date'], y =vertical_concat['open'], color=vertical_concat['company'], line_group=vertical_concat['company'], hover_name=vertical_concat['company'],
        line_shape="spline", render_mode="svg")

fig15.update_xaxes(
    rangeslider_visible=True,
    rangeselector=dict(
        buttons=list([
            dict(count=5, label="5d", step="day", stepmode="backward"),
            dict(count=1, label="1m", step="month", stepmode="backward"),
            dict(count=6, label="6m", step="month", stepmode="backward"),
            dict(count=1, label="YTD", step="year", stepmode="todate"),
            dict(count=1, label="1y", step="year", stepmode="backward"),
            dict(count=5, label="5y", step="year", stepmode="backward"),
            dict(step="all")
        ])
    )
)
fig15.update_layout(xaxis_rangeslider_visible=False)
fig15.update_layout(title_text='Line chart for ACC and Ambuja with selectors')

fig15.show()

Individual line chart for ACC and Ambuja
fig16 = px.line(vertical_concat,x = vertical_concat['date'], 
            y =vertical_concat['open'], color= 'company', 
            facet_col="company", facet_col_wrap=2
        )

fig16.show()

Histogram on date axes
fig17 = px.histogram(df_acc, x=df_acc["date"], y=df_acc["close"], histfunc="avg", title="Histogram on Date Axes")
fig17.update_traces(xbins_size="M1")
fig17.update_xaxes(showgrid=True, ticklabelmode="period", dtick="M1", tickformat="%b
%Y")
fig17.update_layout(bargap=0.1)
fig17.add_trace(go.Scatter(mode="markers", x=df_acc["date"], y=df_acc["close"], name="daily"))


fig17.update_xaxes(
    rangeslider_visible=True,
    rangeselector=dict(
        buttons=list([
            dict(count=5, label="5d", step="day", stepmode="backward"),
            dict(count=1, label="1m", step="month", stepmode="backward"),
            dict(count=6, label="6m", step="month", stepmode="backward"),
            dict(count=1, label="YTD", step="year", stepmode="todate"),
            dict(count=1, label="1y", step="year", stepmode="backward"),
            dict(count=5, label="5y", step="year", stepmode="backward"),
            dict(step="all")
        ])
    )
)

fig17.show()

Area chart for ACC and Ambuja
fig18 = px.area(vertical_concat,x = vertical_concat['date'], y =vertical_concat['open'], color= 'company', line_group='company')


fig18.show()